Weiming Huang
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View article: SILO: Semantic Integration for Location Prediction with Large Language Models
SILO: Semantic Integration for Location Prediction with Large Language Models Open
View article: Geospatial Knowledge Graphs
Geospatial Knowledge Graphs Open
View article: Learning dual context aware POI representations for geographic mapping
Learning dual context aware POI representations for geographic mapping Open
Driven by artificial intelligence technologies, geospatial representation learning has become a new trend to better understand urban systems. Points of Interest (POI), as the current mainstream data in urban studies, plays an important rol…
View article: Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places
Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places Open
Predicting individuals' next locations is a core task in human mobility modelling, with wide-ranging implications for urban planning, transportation, public policy and personalised mobility services. Traditional approaches largely depend o…
View article: Unveiling optimal SDG pathways: an innovative automated recommendation approach integrating graph pruning, intent graph, and attention mechanism
Unveiling optimal SDG pathways: an innovative automated recommendation approach integrating graph pruning, intent graph, and attention mechanism Open
The recommendation of Sustainable Development Pathways (SDPs) is crucial for achieving the United Nations Sustainable Development Goals (SDGs) at regional level. However, traditional recommendation algorithms struggle with two key challeng…
View article: Fairness identification of large language models in recommendation
Fairness identification of large language models in recommendation Open
View article: Incorporating dynamic mode decomposition and domain adversarial training for cross-domain SOH estimation of lithium-ion batteries
Incorporating dynamic mode decomposition and domain adversarial training for cross-domain SOH estimation of lithium-ion batteries Open
View article: Self-Supervised Representation Learning for Geospatial Objects: A Survey
Self-Supervised Representation Learning for Geospatial Objects: A Survey Open
View article: Incorporating dynamic mode decomposition and domain adversarial training for cross-domain SOH estimation of lithium-ion batteries
Incorporating dynamic mode decomposition and domain adversarial training for cross-domain SOH estimation of lithium-ion batteries Open
View article: Fairness Identification of Large Language Models in Recommendation
Fairness Identification of Large Language Models in Recommendation Open
Ensuring fairness in recommendation systems necessitates that models do not discriminate against users based on demographic information such as gender and age. Current fairness strategies often apply a unified fairness intervention, presum…
View article: City Foundation Models for Learning General Purpose Representations from OpenStreetMap
City Foundation Models for Learning General Purpose Representations from OpenStreetMap Open
View article: Urban region representation learning with human trajectories: a multi-view approach incorporating transition, spatial, and temporal perspectives
Urban region representation learning with human trajectories: a multi-view approach incorporating transition, spatial, and temporal perspectives Open
Mining latent information from human trajectories for understanding our cities has been persistent endeavors in urban studies and spatial information science. Many previous studies relied on manually crafted features and followed a supervi…
View article: Self-Supervised Representation Learning for Geospatial Objects: A Survey
Self-Supervised Representation Learning for Geospatial Objects: A Survey Open
The proliferation of various data sources in urban and territorial environments has significantly facilitated the development of geospatial artificial intelligence (GeoAI) across a wide range of geospatial applications. However, geospatial…
View article: Learning-Based Super-Resolution Imaging of Turbulent Flames in Both Time and 3D Space Using Double GAN Architectures
Learning-Based Super-Resolution Imaging of Turbulent Flames in Both Time and 3D Space Using Double GAN Architectures Open
This article presents a spatiotemporal super-resolution (SR) reconstruction model for two common flame types, a swirling and then a jet flame, using double generative adversarial network (GAN) architectures. The approach develops two sets …
View article: Defining three ferroptosis-based molecular subtypes and developing a prognostic risk model for high-grade serous ovarian cancer
Defining three ferroptosis-based molecular subtypes and developing a prognostic risk model for high-grade serous ovarian cancer Open
Our results could improve the understanding of ferroptosis in OV, providing promising insights for the clinical targeted therapy for the cancer.
View article: Urban Region Embedding via Multi-View Contrastive Prediction
Urban Region Embedding via Multi-View Contrastive Prediction Open
Recently, learning urban region representations utilizing multi-modal data (information views) has become increasingly popular, for deep understanding of the distributions of various socioeconomic features in cities. However, previous meth…
View article: On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper)
On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper) Open
Large pre-trained models, also known as foundation models (FMs), are trained in a task-agnostic manner on large-scale data and can be adapted to a wide range of downstream tasks by fine-tuning, few-shot, or even zero-shot learning. Despite…
View article: LAMP: A Language Model on the Map
LAMP: A Language Model on the Map Open
Large Language Models (LLMs) are poised to play an increasingly important role in our lives, providing assistance across a wide array of tasks. In the geospatial domain, LLMs have demonstrated the ability to answer generic questions, such …
View article: Joint Modeling of Citation Networks and User Preferences for Academic Tagging Recommender System
Joint Modeling of Citation Networks and User Preferences for Academic Tagging Recommender System Open
In the tag recommendation task on academic platforms, existing methods disregard users' customized preferences in favor of extracting tags based just on the content of the articles.Besides, it uses co-occurrence techniques and tries to com…
View article: Urban Region Embedding via Multi-View Contrastive Prediction
Urban Region Embedding via Multi-View Contrastive Prediction Open
Recently, learning urban region representations utilizing multi-modal data (information views) has become increasingly popular, for deep understanding of the distributions of various socioeconomic features in cities. However, previous meth…
View article: City Foundation Models for Learning General Purpose Representations from OpenStreetMap
City Foundation Models for Learning General Purpose Representations from OpenStreetMap Open
Pre-trained Foundation Models (PFMs) have ushered in a paradigm-shift in Artificial Intelligence, due to their ability to learn general-purpose representations that can be readily employed in a wide range of downstream tasks. While PFMs ha…
View article: Uncovering the association between traffic crashes and street-level built-environment features using street view images
Uncovering the association between traffic crashes and street-level built-environment features using street view images Open
Investigating the relationship between built environment factors and roadway safety is crucial for preventing road traffic accidents. Although studies have analyzed traffic-related built environment factors based on pre-determined zonal un…
View article: Urban Region Representation Learning with OpenStreetMap Building Footprints
Urban Region Representation Learning with OpenStreetMap Building Footprints Open
The prosperity of crowdsourcing geospatial data provides increasing opportunities to understand our cities. In particular, OpenStreetMap (OSM) has become a prominent vault of geospatial data on the Web. In this context, learning urban regi…
View article: Towards an Integrated View of Semantic Annotation for POIs with Spatial and Textual Information
Towards an Integrated View of Semantic Annotation for POIs with Spatial and Textual Information Open
Categories of Point of Interest (POI) facilitate location-based services from many aspects like location search and POI recommendation. However, POI categories are often incomplete and new POIs are being consistently generated, this rises …
View article: Safety and feasibility of preferential manual bronchoplasty in 2–3 cm single‐port video‐assisted thoracoscopic lobectomy
Safety and feasibility of preferential manual bronchoplasty in 2–3 cm single‐port video‐assisted thoracoscopic lobectomy Open
Background This retrospective study aimed to compare preferential manual bronchoplasty (PMB) and mechanical stapler closure (MSC) of the bronchial stump after 2–3 cm single‐port (SP) video‐assisted thoracoscopic surgery (VATS) lobectomy in…
View article: Mining Geospatial Relationships from Text
Mining Geospatial Relationships from Text Open
A geospatial Knowledge Graph (KG) is a heterogeneous information network, capable of representing relationships between spatial entities in a machine-interpretable format, and has tremendous applications in logistics and social networks. E…
View article: A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation
A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation Open
Similarity measurement has been a prevailing research topic in geographic information science. Geometric similarity measurement in scaling transformation (GSM_ST) is critical to ensure spatial data quality while balancing detailed informat…
View article: On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence
On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence Open
Large pre-trained models, also known as foundation models (FMs), are trained in a task-agnostic manner on large-scale data and can be adapted to a wide range of downstream tasks by fine-tuning, few-shot, or even zero-shot learning. Despite…
View article: Sub-sampled dataset for Shenzhen (HGI region embedding example dataset)
Sub-sampled dataset for Shenzhen (HGI region embedding example dataset) Open
Please download it to put in /Data if you want to learn region embeddings for Shenzhen. Note that this is a sub-sampled dataset for Shenzhen (first 820 regions), as the entire dataset takes a long time to train.
View article: A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation
A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation Open
The data and code were used for the geometric similarity measurement of drainage networks supported by a graph autoencoder network.